Performance evaluation of two commercial chemiluminescence NOx analysers according to European Standard EN 14211

According to Directive 2008/50/EC, all equipment used for NO(x) fixed measurements must comply with the reference method or equivalent by 11 June 2013. Up to that date, non-type-approved equipment can continue to be used in air monitoring networks and will probably also be used in air pollution studies even after that date. In this context, it is advisable to know how these "old" measuring instruments respond to the requirements of European Standard EN 14211: 2005: Ambient Air Quality--Standard method for the measurement of the concentration of nitrogen dioxide and nitrogen monoxide by chemiluminescence. In this work, we carry out a thorough performance evaluation of two commercial NO(x) analysers, both purchased before 2010, according to the mentioned Standard. Results show that water vapour interference is one of the most important disconformities with this Standard. The expanded uncertainty estimation of both analysers was below the quality objective of the above-mentioned Directive (15%); however, this calculation was performed by applying some modifications to the proposed model of Standard EN 14211. These modifications are also discussed in the paper.     

Modeling of SO<Subscript>2</Subscript> distribution in Istanbul using artificial neural networks

Urban air pollution is a growing problem in developing countries. Some compounds especially sulphur dioxide (SO₂) is considered as typical indicators of the urban air quality. Air pollution modeling and prediction have great importance in preventing the occurrence of air pollution episodes and provide sufficient time to take the necessary precautions. Recently, various stochastic image-processing algorithms such as Artificial Neural Network (ANN) are applied to environmental engineering. ANN structure employs input, hidden and output layers. Due to the complexity of the problem, as the number of input–output parameters differs, ANN model settings such as the number of neurons of these layers changes. The ability of ANN models to learn, particularly capability of handling large amounts (or sets) of data simultaneously as well as their fast response time, are invariably the characteristics desired for predictive and forecasting purposes. In this paper, ANN models have been used to predict air pollutant parameter in meteorological considerations. We have especially focused on modeling of SO₂ distribution and predicting its future concentration in Istanbul, Turkey. We have obtained data sets including meteorological variables and SO₂ concentrations from Istanbul-Florya meteorological station and Istanbul-Yenibosna air pollution station. We have preferred three-layer perceptron type of ANN which consists of 10, 22 and 1 neurons for input, hidden and output layers, respectively. All considered parameters are measured as daily mean. The input parameters are: SO₂ concentration, pressure, temperature, humidity, wind direction, wind speed, strength of sunshine, sunshine, cloudy, rainfall and output parameter is the future prediction of SO₂. To evaluate the performance of ANN model, our results are compared to classical nonlinear regression methods. The over all system finds an optimum correlation between input–output variables. Here, the correlation parameter, r is 0.999 and 0.528 for training and test data. Thus in our model, the trend of SO₂ is well estimated and seasonal effects are well represented. As a result, we conclude that ANN is one of the compromising methods in estimation of environmental complex air pollution problems.     

Short-Term Forecasting of Nitrogen Dioxide (NO<Subscript>2</Subscript>) Levels Using a Hybrid Statistical and Air Mass History Modelling Approach

A novel hybrid model has been developed to support the provision of real-time air quality forecasts. Statistical techniques have been applied in parallel with air mass history modelling to provide an efficient and accurate forecasting system with the ability to identify high NO₂ events, which tend to be the episodes of most significance in Ireland. Air mass history modelling and k-means clustering are used to identify air mass types that lead to high NO₂ levels in Ireland. Trajectory matching techniques allow data associated with these air masses to be partitioned during model development. Non-parametric regression (NPR) has been applied to describe nonlinear variations in concentration levels with wind speed, direction and season and produce a set of linearized factors which, together with other meteorological variables, are employed as inputs to a multiple linear regression. The model uses an innovative integrated approach to combine the NPR with the air mass history modelling results. On validation, a correlation coefficient of 0.75 was obtained, and 91 % of daily maximum (hourly averaged) NO₂ predictions were within a factor of two of the measured value. High pollution events were well captured, as indicated by strong agreement between measured and modelled high percentile values. The model requires only simple input data, does not require an emission inventory and utilises very low computational resources. It represents an accurate and efficient means of producing real-time air quality forecasts and, when used in combination with forecaster experience, is a useful tool for identifying periods of poor air quality 24 h in advance. The hybrid approach outlined in this paper can easily be applied to produce high-quality forecasts of both NO₂ and additional pollutants at new locations/countries where historical monitoring data are available.     

Comparative validation of amperometric and optical analyzers of dissolved oxygen: a case study

A comprehensive comparative validation for two different types of dissolved oxygen (DO) analyzers, amperometric and optical, is presented on two representative commercial DO analyzers. A number of performance characteristics were evaluated including drift, intermediate precision, accuracy of temperature compensation, accuracy of reading (under different measurement conditions), linearity, flow dependence of the reading, repeatability (reading stability), and matrix effects of dissolved salts. The matrix effects on readings in real samples were evaluated by analyzing the dependence of the reading on salt concentration (at saturation concentration of DO). The analyzers were also assessed in DO measurements of a number of natural waters. The uncertainty contributions of the main influencing parameters were estimated under different experimental conditions. It was found that the uncertainties of results for both analyzers are quite similar but the contributions of the uncertainty sources are different. Our results imply that the optical analyzer might not be as robust as is commonly assumed; however, it has better reading stability, lower stirring speed dependence, and typically requires less maintenance. On the other hand, the amperometric analyzer has a faster response and wider linear range. Both analyzers seem to have issues with the accuracy of temperature compensation. The approach described in this work will be useful to practitioners carrying out DO measurements for ensuring reliability of their measurements.     

Demonstrating PM<Subscript>2.5</Subscript> and road-side dust pollution by heavy metals along Thika superhighway in Kenya,sub-Saharan Africa

This study assessed the level of heavy metal in roadside dust and PM_2.5 mass concentrations along Thika superhighway in Kenya. Thika superhighway is one of the busiest roads in Kenya, linking Thika town with Nairobi. Triplicate road dust samples collected from 12 locations were analysed for lead (Pb), chromium (Cr), cadmium (Cd), nickel (Ni), zinc (Zn), and copper (Cu) using atomic absorption spectrophotometry (AAS). PM_2.5 samples were collected on pre-weighed Teflon filters using a BGI personal sampler and the filters were then reweighed. The ranges of metal concentrations were 39–101 μg/g for Cu, 95–262 μg/g for Zn, 9–28 μg/g for Cd, 14–24 μg/g for Ni, 13–30 μg/g for Cr, and 20–80 μg/g for Pb. The concentrations of heavy metals were generally highly correlated, indicating a common anthropogenic source of the pollutants. The results showed that the majority of the measured heavy metals were above the background concentration, and in particular, Cd, Pb, and Zn levels indicated moderate to high contamination. Though not directly comparable due to different sampling timeframes (8 h in this study and 24 h for guideline values), PM_2.5 for all sites exceeds the daily WHO PM_2.5 guidelines of 25 μg/m³. This poses a health risk to people using and working close to Thika superhighway, for example, local residents, traffic police, street vendors, and people operating small businesses. PM_2.5 levels were higher for sites closer to Nairobi which could be attributed to increased vehicular traffic towards Nairobi from Thika. This study provides some evidence of the air pollution problem arising from vehicular traffic in developing parts of the world and gives an indication of the potential health impacts. It also highlights the need for source apportionment studies to determine contributions of anthropogenic emissions to air pollution, as well as long-term sampling studies that can be used to fully understand spatiotemporal patterns in air pollution within developing regions.     

Seasonal variations of air pollutant concentrations within Krasnoyarsk City

This paper examines the significant differences in seasonal variations of criteria pollutant concentrations in various parts of a large urban area. These differences are caused by the microclimatic heterogeneity of the city and show the influence of breeze and orographic-type circulations on urban air pollution. The temperature heterogeneity of Krasnoyarsk territory during the winter leads to an increase of 150% in CO air pollution levels in the central part of city. During the summer the orographical heterogeneity of Krasnoyarsk City leads to increases of up to 400% in air pollution for different areas.     

BIOMONITORING OF AIR POLLUTION IN A SEASONALLY DRY TROPICAL SUBURBAN AREA USING WHEAT TRANSPLANTS

Air pollution has been identified as a serious problem throughout the world which causes tremendous loss to the crops by affecting plant growth and yield. Earlier, air pollution was restricted to urban and industrial regions. Over the last few decades, however, it has become evident that pollutants can be transported over long distances and hence their impact may be felt widely over rural areas. The present study was conducted to evaluate the impact of urban air pollution on suburban agriculture with respect to the changes in photosynthetic rate, stomatal conductance, water-use efficiency, plant height, numbers of tillers, leaves, ears and seeds, chlorophyll, carotenoid, protein, phenol, ascorbic acid, nitrogen and sulphate-sulphur contents and seed weight of pot-grown wheat plants (Triticum aestivum var. HUW 468) kept at different sites around Varanasi city receiving varying levels of pollution load. Mean concentrations of were monitored. The study clearly showed that plants are negatively affected by the ambient levels of air pollutants. Reduction in various parameters directly corresponded with the air pollution levels at different sites.     

Determination of hydrogen peroxide in workplace air: interferences and method validation

A dynamic system for the generation of stable hydrogen peroxide test atmospheres was applied to the evaluation of samplers used for the determination of hydrogen peroxide in workplace air. The system is able to generate gas mixtures of between 0.1 and 10 ppm at different combinations of relative humidity (20-80%) and temperature (10-30 degrees C). Gaseous hydrogen peroxide is sampled on glass filters impregnated with Ti(IV) chloride and sulfuric acid and analyzed by UV spectroscopy. An interference was observed due to the acid catalyzed decomposition of peroxyacetic acid to hydrogen peroxide. This was significantly reduced by applying high sample flow rates and by lowering the concentration of sulfuric acid. The performance of the sampler and sources of uncertainties were tested according to the European Standard EN 1076.     

What Forces Dictate the Design of Pollution Monitoring Networks?

The US Environmental Protection Agency maintains networks of pollution monitors for two basic purposes: to check and enforce the attainment of national ambient air quality standards (NAAQS) and to provide useful data for studying pollution and its effects. These purposes imply conflicting criteria for the locations of a limited number of monitors. To check the attainment of standards, monitors are placed where pollution levels are highest. Monitors are not required where standards have always been met and there are no new pollution sources. To provide useful data for studying pollution and its effects, monitors would be placed to observe outcomes under a variety of pollution levels. This study asks the following questions. What factors affect when a monitor is retired from the network? What drives the decision to add a new site? What causes year-to-year changes in the number of monitors? We tackle these questions with a particular focus on the role of regulatory compliance and pollution levels in the context of monitors for tropospheric ozone (O₃). Using a panel dataset of monitors in the contiguous US spanning the years 1993 to 2011, we find that the peak O₃ readings in the prior period are significantly associated with the regulator’s decision of whether to add or to drop a monitor in the following period. While compliance with the NAAQS for O₃ is not consistently associated with network composition, compliance with the PM_2.5 NAAQS does appear to affect changes to the network.     

2015—2017年江苏省秋、冬季空气质量状况

采用2015—2017年秋、冬季江苏省环境空气质量监测数据,从空气质量优良(达标)率、首要污染物、主要污染物浓度分析空气质量现状及特点。结果表明,江苏省秋、冬季空气质量优良(达标)率在60%左右,其中沿海地区空气质量达标率最高(71.1%),西北地区达标率最差(52.2%)。污染日的首要污染物主要为PM 2.5,占比高达91.5%。ρ(PM2.5)/ρ(PM 10)存在地区差异,江苏西北地区扬尘源贡献较大,江苏南部地区的二次颗粒物贡献更明显。ρ(NO2)/ρ(SO2)逐年持续升高,表明大气污染类型从燃煤性污染转变为复合型污染。     

北京市2013年1月一次空气重污染过程分析

采用数值模式与观测资料相结合的方式，对北京市2013年1月9～15日一次空气重污染过程的大气环境背景、气象条件和形成原因进行了初步分析。结果表明，此次重污染过程北京市空气质量从9日的二级跳至10日五级重度污染，11日一13日空气质量维持连续3d严重污染，14日降为重度污染，15日转为轻度污染；重污染过程期间10—14日P（PM2.5）平均值为323μg／m。，平均风速为1．47m／s，平均相对湿度为73．6％，24h变温基本为一2．72～2．68℃，24h平均变压为一3．65～2．63hPa。指出，此次重污染过程与当地气象条件密切相关，稳定的大气环流形势为污染的持续提供了大气环流背景，风速较小、湿度较大、边界层较低、持续逆温是造成重污染的主要原因，地面风场辐合及边界层下沉运动是造成重污染的重要原因。     

Public-Health Impact of Outdoor Air Pollution in Russia

Based on the well-known approaches to risk assessment, estimates of the number of attributable deaths caused by atmospheric air pollution in the towns of Russia have been obtained. The data of daily monitoring of air pollution in 1993 and 1998 carried out by Rosgidromet (Weather Service of Russia) were used for assessment. The epidemiology-based exposure–response function for a 10 g/m³ increase in particulate matter PM₁₀ was used to assess the attributable number of cases of deaths in Russia. The EPA approach was applied to derive the risk of carcinogenesis caused by outdoor carcinogens controlled by Rosgidromet. In the present paper, it has been shown that up to 219–233 thousands of premature deaths or 15–17% out of the total annual mortality might be caused by air pollution in Russia. The data are given on a possible contribution of various carcinogens controlled by Rosgidromet at the stations of constant observation to the total mortality caused by atmospheric pollution. On the whole, the number of people that fell ill with cancer as a result of exposure to all the carcinogens present in the atmosphere can be assessed within the range of 2000–4000 humans. This assessment estimates the public-health impacts of air pollution. At the present time, we have no information concerning the degree of universality of the exposure–response function for PM₁₀ and its sensitivity to a change in social-demographic indicators. Nevertheless, the assessments, given in the present work, make it possible to obtain important information concerning the possible scale of health-outcome due to atmospheric pollution for the population of Russia.     

Development of a method for bacteria and virus recovery from heating, ventilation, and air conditioning (HVAC) filters

The aim of the work presented here is to study the effectiveness of building air handling units (AHUs) in serving as high volume sampling devices for airborne bacteria and viruses. An HVAC test facility constructed according to ASHRAE Standard 52.2-1999 was used for the controlled loading of HVAC filter media with aerosolized bacteria and virus. Nonpathogenic Bacillus subtilis var. niger was chosen as a surrogate for Bacillus anthracis. Three animal viruses; transmissible gastroenteritis virus (TGEV), avian pneumovirus (APV), and fowlpox virus were chosen as surrogates for three human viruses; SARS coronavirus, respiratory syncytial virus, and smallpox virus; respectively. These bacteria and viruses were nebulized in separate tests and injected into the test duct of the test facility upstream of a MERV 14 filter. SKC Biosamplers upstream and downstream of the test filter served as reference samplers. The collection efficiency of the filter media was calculated to be 96.5 +/- 1.5% for B. subtilis, however no collection efficiency was measured for the viruses as no live virus was ever recovered from the downstream samplers. Filter samples were cut from the test filter and eluted by hand-shaking. An extraction efficiency of 105 +/- 19% was calculated for B. subtilis. The viruses were extracted at much lower efficiencies (0.7-20%). Our results indicate that the airborne concentration of spore-forming bacteria in building AHUs may be determined by analyzing the material collected on HVAC filter media, however culture-based analytical techniques are impractical for virus recovery. Molecular-based identification techniques such as PCR could be used.     

Relationships of relative humidity with PM<Subscript>2.5</Subscript> and PM<Subscript>10</Subscript> in the Yangtze River Delta,China

Severe particulate matter (PM, including PM_2.5 and PM₁₀) pollution frequently impacts many cities in the Yangtze River Delta (YRD) in China, which has aroused growing concern. In this study, we examined the associations between relative humidity (RH) and PM pollution using the equal step-size statistical method. Our results revealed that RH had an inverted U-shaped relationship with PM_2.5 concentrations (peaking at RH = 45–70%), and an inverted V-shaped relationship (peaking at RH = 40 ± 5%) with PM₁₀, SO₂, and NO₂. The trends of polluted-day number significantly changed at RH = 70%. The very-dry (RH < 45%), dry (RH = 45–60%) and low-humidity (RH = 60–70%) conditions positively affected PM_2.5 and exerted an accumulation effect, while the mid-humidity (RH = 70–80%), high-humidity (RH = 80–90%), and extreme-humidity (RH = 90–100%) conditions played a significant role in reducing particle concentrations. For PM₁₀, the accumulation and reduction effects of RH were split at RH = 45%. Moreover, an upward slope in the PM_2.5/PM₁₀ ratio indicated that the accumulation effects from increasing RH were more intense on PM_2.5 than on PM₁₀, while the opposite was noticed for the reduction effects. Secondary transformations from SO₂ and NO₂ to sulfate and nitrate were mainly responsible for PM_2.5 pollution, and thus, controlling these precursors is effective in mitigating the PM pollution in the YRD, especially during winter. The conclusions in this study will be helpful for regional air-quality management.     

一氧化氮标准气体中二氧化氮杂质FTIR定量方法研究及标气质量分析

一氧化氮标准气体在我国空气质量监测工作中广泛用于氮氧化物分析仪的校准,标准气体的质量对环境空气中氮氧化物的测量结果也有着显著的影响.利用傅里叶变换红外光谱仪建立了一套精确测量低浓度二氧化氮方法,并对一氧化氮标准气体产品中二氧化氮杂质进行了测量.结果显示有少部分样品中存在较高浓度的二氧化氮杂质.进一步讨论了可能导致一氧化...     

Real time remote monitoring of air pollutants and their online transmission to the web using internet protocol

Recent advances in both information and sensor technologies have enabled the development of Real Time Remote Monitoring (RTRM) capabilities for environmental management. An online and real time remote monitoring system for air pollution has been designed and installed at a traffic police station at Punjagutta in Hyderabad, India. The system is optimized using electrochemical sensors and a real time particulate matter analyzer. The system also monitors meteorological parameters such as temperature, humidity, rainfall, barometric pressure, wind speed and wind direction. The system periodically monitors both pollution and meteorological parameters at pre- programmed intervals of hr during peak periods and 1 hr during non peak periods of the day and continuously uploads to a predestinated web site (www.appcb.org/home.htm) using File Transfer Protocol. The web site renders a quick, simple and graphical display of air pollution levels and meteorological parameters and their significance to humans. The present paper highlights design considerations of a pollution monitoring system, system hardware and software requirements and practical limitations and future directions for real time remote monitoring of air pollution.     

Temperature effect of tapered element oscillating microbalance (TEOM) system measuring semi-volatile organic particulate matter

The tapered element oscillating microbalance (TEOM) system is widely used to measure continuous particle mass concentrations in air quality networks. However, the semi-volatile aerosol material is lost under normal operation conditions (50 °C). This study has evaluated the error in the organic fraction of the TEOM-measured secondary organic aerosols formed from the degradation of biogenic pollutants. Experiments were carried out under controlled, water-free conditions in a fully equipped, high volume atmospheric simulator--the European PhotoReactor (EUPHORE). The ozonolysis of α-pinene, β-pinene and limonene provided a reproducible source of organic aerosol. Particulate matter concentration profiles were registered for different TEOM operating temperatures. When these values were compared with values from a filter-based gravimetric method and a scanning mobility particle sizer (SMPS), they showed that the differences between monitoring systems increased with increasing TEOM temperature. According to our results, when the TEOM is operated at 50 °C, it fails to measure 32-46% of the organic particulate material, depending on the aerosol precursor. This study has also identified and quantified the multi-oxygenated organic compounds lost in the TEOM monitoring by using a method based on the gas chromatography-mass spectrometry technique. Important losses have been calculated for relevant ambient aerosol compounds such as pinonic acid, pinonaldehyde, norpinone and limonalic acid. In conclusion, the present study has demonstrated that a high operating temperature of the TEOM monitor reduces the humidity interference but underestimates the semi-volatile organic fraction.     

Health impact assessment of air pollution using a dynamic exposure profile: Implications for exposure and health impact estimates

In both ambient air pollution epidemiology and health impact assessment an accurate assessment of the population exposure is crucial. Although considerable advances have been made in assessing human exposure outdoors, the assessments often do not consider the impact of individual travel behavior on such exposures.Population-based exposures to NO₂ and O₃ using only home addresses were compared with models that integrate all time-activity patterns—including time in commute—for Flanders and Brussels. The exposure estimates were used to estimate the air pollution impact on years of life lost due to respiratory mortality.Health impact of NO₂ using an exposure that integrates time-activity information was on average 1.2% higher than when assuming that people are always at their home address. For ozone the overall estimated health impact was 0.8% lower. Local differences could be much larger, with estimates that differ up to 12% from the exposure using residential addresses only. Depending on age and gender, deviations from the population average were seen.Our results showed modest differences on a regional level. At the local level, however, time-activity patterns indicated larger differences in exposure and health impact estimates, mainly for people living in more rural areas. These results suggest that for local analyses the dynamic approach can contribute to an improved assessment of the health impact of various types of pollution and to the understanding of exposure differences between population groups.     

Biochemical changes in plant leaves as a biomarker of pollution due to anthropogenic activity

The air pollution due to anthropogenic activities seriously affected human life, vegetation, and heritage as well. The vegetation cover in and around the city mitigates the air pollution by acting as a sink for pollution. An attempt was made to evaluate biochemical changes occurred in four selected plant species, namely Azadirachta indica, Mangifera indica, Delonix regia, and Cassia fistula of residential, commercial, and industrial areas of Nagpur city in India. It was observed that the correlated values of air pollutants and plant leaves characteristics alter foliar biochemical features (i.e., chlorophyll and ascorbic acid content, pH and relative water content) of plants due to air pollution. The changes in air pollution tolerance index of plants was also estimated which revealed that these plants can be used as a biomarker of air pollution.     

室内空气中甲醛测定比对试验的探讨

为了检验化学酚试剂比色法与便携式甲醛测定仪测定室内空气中甲醛方法间有无显著性差异，用2种方法做了比对试验，并对2种方法的相关性、精密性进行了分析。结果表明，2种分析方法无显著性差异。便携式甲醛分析仪具有操作简单、携带方便、直观性强等优点，有利于民用建筑室内环境中甲醛的测定。